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Smoking cessation programs for pregnant women: Contingency management

Health Care: Maternal and Infant Health
Benefit-cost methods last updated December 2023.  Literature review updated December 2016.
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Contingency management is a supplement to counseling treatment that rewards participants for attending treatment and/or abstaining from substance use. The intervention reviewed here focused on women who smoked during pregnancy who were also receiving smoking cessation counseling, and provided rewards contingent on quitting and remaining abstinent. Rewards were in the form of vouchers that could be exchanged for goods. Individuals received treatment for an average of three months.
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2022). The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $1,128 Benefits minus costs $11,424
Participants $1,172 Benefit to cost ratio $47.33
Others $641 Chance the program will produce
Indirect $8,730 benefits greater than the costs 98%
Total benefits $11,670
Net program cost ($247)
Benefits minus cost $11,424

^WSIPP’s benefit-cost model does not monetize this outcome.

***We report this outcome twice: once for mothers (designated as the primary participant) and once for infants (designated as the secondary participant). We do this because the outcome is associated with costs and benefits for both mothers and infants, and the amount of the cost or benefit is different for mothers than it is for infants.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease over time. For those effect sizes, we estimate outcome-based adjustments which we apply between the first time ES is estimated and the second time ES is estimated. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age Primary or secondary participant No. of effect sizes Treatment N Adjusted effect sizes(ES) and standard errors(SE) used in the benefit - cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
27 Primary 5 457 -0.340 0.130 27 0.000 0.000 28 -0.340 0.009
27 Primary 4 151 -0.494 0.217 27 0.000 0.000 28 -0.494 0.023
27 Primary 4 422 -0.498 0.121 27 -0.498 0.121 37 -0.498 0.001
27 Primary 7 516 -0.752 0.110 27 n/a n/a n/a -0.752 0.001
1 Secondary 4 151 -0.339 0.213 1 0.000 0.000 2 -0.339 0.112
1 Secondary 5 457 -0.340 0.130 1 0.000 0.000 2 -0.340 0.009
1 Secondary 4 151 -0.494 0.217 1 0.000 0.000 2 -0.494 0.023
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Low birthweight birth Health care associated with low birthweight births $53 $2 $53 $27 $135
Subtotals $53 $2 $53 $27 $135
From secondary participant
Low birthweight birth Infant mortality $486 $1,146 $0 $8,532 $10,164
NICU admission Health care associated with NICU admissions $588 $24 $588 $294 $1,494
Subtotals $1,074 $1,170 $588 $8,826 $11,658
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($123) ($123)
Totals $1,128 $1,172 $641 $8,730 $11,670
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $446 2016 Present value of net program costs (in 2022 dollars) ($247)
Comparison costs $237 2016 Cost range (+ or -) 30%
The per-participant cost of treatment is based on average provider time reported in studies, plus the average incentive amount received by treatment participants. Physician/therapist time reported for smoking cessation counseling was multiplied by the Medicaid reimbursement rate for tobacco cessation for pregnant clients, reported by the Washington State Health Care Authority for physician-related/professional services. Provider time reported for abstinence monitoring during contingency management was calculated using the mean hourly wage for Washington State reported by the Bureau of Labor Statistics for the appropriate provider, and wages were increased by a factor of 1.441 to account for the cost of employee benefits. Costs were obtained from Heil et al. (2008), Higgins et al. (2004), Higgins et al. (2014), Ondersma et al. (2012), Tappin et al. (2015), and Tuten et al. (2012).
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Heil, S.H., Higgins, S.T., Bernstein, I.M., Solomon, L.J., Rogers, R.E., Thomas, C.S., . . . Lynch, M.E. (2008). Effects of voucher-based incentives on abstinence from cigarette smoking and fetal growth among pregnant women. Addiction 103(6), 1009-18.

Higgins, S.T., Heil, S.H., Solomon, L.J., Bernstein, I.M., Lussier, J.P., Abel, R.L., . . . Badger, G.J. (2004). A pilot study on voucher-based incentives to promote abstinence from cigarette smoking during pregnancy and postpartum. Nicotine & Tobacco Research, 6(6), 1015-20.

Higgins, S.T., Washio, Y., Lopez, A.A., Heil, S.H., Solomon, L.J., Lynch, M.E., . . . Bernstein, I.M. (2014). Examining two different schedules of financial incentives for smoking cessation among pregnant women. Preventive Medicine, 68, 51-57.

Ondersma, S.J., Svikis, D.S., Lam, P.K., Connors-Burge, V.S., Ledgerwood, D.M., & Hopper, J.A. (2012). A randomized trial of computer-delivered brief intervention and low-intensity contingency management for smoking during pregnancy. Nicotine & Tobacco Research, 14(3), 351-60.

Tappin, D., Bauld, L., Purves, D., Boyd, K., Sinclair, L., MacAskill, S., . . . Cessation in Pregnancy Incentives Trial Team. (2015). Financial incentives for smoking cessation in pregnancy: randomized controlled trial. BMJ (Clinical Research Ed.), 350, h134.

Tuten, M., Fitzsimons, H., Chisolm, M.S., Nuzzo, P.A., & Jones, H.E. (2012). Contingent incentives reduce cigarette smoking among pregnant, methadone-maintained women: results of an initial feasibility and efficacy randomized clinical trial. Addiction, 107(10), 1868-1877.